Award Data

"Complex analysis of intelligence imagery is crucial to the missions of intelligence organizations, yet remains constrained by labor-intensive, time-consuming visual search of large volumes of imagery. Many algorithms have been developed to automaticallyidentify regions of interest in large, complex sets of imagery, yet the utility of such algorithms is limited by the fact that human analysts dete ...

Through previous grant awards from IES, researchers developed Graspable Math, a tablet-based intervention where middle and high school students create and manipulate complex expressions for basic operations as well as equations and equations systems and inequalities. In this project, the team will develop a prototype of Graspable Math Activities, an app with novel kinds of algebra practice and ass ...

This SBIR Phase I project proposes a probabilistic approach to determine a vehicles location using onboard video sensors and foundationalmap data. The system does not rely on only one type of information source, instead it combines proposals from a variety of locationestimators to find a vehicles location in GPS-denied environments.The system takes advantage of recent advancements in computer visi ...

Deep Learning Analytics (DLA) will develop the Deep-False Alarm Suppression Technique (D-FAST) algorithm that uses state of the art and

This SBIR Phase II project will develop biologically inspired computational models and algorithms to enable low-shot and one-shot detectionof objects-of-interest in remote sensing imagery. The Phase II effort will build upon our Phase I work including multi-scale representationlearning framework and deep-learning based feature extraction and matching techniques for low-shot target detection. The P ...